OBJECTIVE This study investigated whether the ability to utilize statistical regularities from fluent speech and map potential words to meaning at 18-months predicts vocabulary at 18- and again at 24-months. METHODS Eighteen-month-olds (N = 47) were exposed to an artificial language with statistical regularities within the speech stream, then participated in an object-label learning task. Learning was measured using a modified looking-while-listening eye-tracking design. Parents completed vocabulary questionnaires when their child was 18-and 24-months old. RESULTS Ability to learn the object-label pairing for words after exposure to the artificial language predicted productive vocabulary at 24-months and amount of vocabulary change from 18- to 24 months, independent of non-verbal cognitive ability, socio-economic status (SES) and/or object-label association performance. CONCLUSIONS Eighteen-month-olds' ability to use statistical information derived from fluent speech to identify words within the stream of speech and then to map the "words" to meaning directly predicts vocabulary size at 24-months and vocabulary change from 18 to 24 months. The findings support the hypothesis that statistical word segmentation is one of the important aspects of word learning and vocabulary acquisition in toddlers.